Overview

Brought to you by YData

Dataset statistics

Number of variables	26
Number of observations	3891
Missing cells	27742
Missing cells (%)	27.4%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	3.3 MiB
Average record size in memory	882.0 B

Variable types

Text	3
Categorical	16
Numeric	7

Alerts

`cant_apercibimientos` has constant value "1.0"	Constant
`cant_MontoLimite` has constant value "1.0"	Constant
`cluster_k_4` has constant value "1"	Constant
`Estado` is highly overall correlated with `periodo_preinscripcion`	High correlation
`TipoSocietario` is highly overall correlated with `periodo_preinscripcion`	High correlation
`anio_preinscripcion` is highly overall correlated with `antiguedad` and 1 other fields	High correlation
`antiguedad` is highly overall correlated with `anio_preinscripcion` and 1 other fields	High correlation
`cant_Apoderado` is highly overall correlated with `cant_autenticado` and 4 other fields	High correlation
`cant_antecedentes` is highly overall correlated with `cant_autenticado` and 1 other fields	High correlation
`cant_autenticado` is highly overall correlated with `cant_Apoderado` and 4 other fields	High correlation
`cant_noAutenticado` is highly overall correlated with `cant_Apoderado` and 4 other fields	High correlation
`cant_procesos_adjudicado` is highly overall correlated with `cant_socios` and 1 other fields	High correlation
`cant_representante` is highly overall correlated with `cant_sinMontoLimite` and 4 other fields	High correlation
`cant_sinMontoLimite` is highly overall correlated with `cant_Apoderado` and 4 other fields	High correlation
`cant_socios` is highly overall correlated with `cant_Apoderado` and 8 other fields	High correlation
`cant_suspensiones` is highly overall correlated with `cant_antecedentes` and 1 other fields	High correlation
`dmonto_total_adjudicado` is highly overall correlated with `cant_representante` and 1 other fields	High correlation
`dtotal_articulos_provee` is highly overall correlated with `periodo_preinscripcion`	High correlation
`monto_total_adjudicado` is highly overall correlated with `cant_noAutenticado` and 2 other fields	High correlation
`periodo_preinscripcion` is highly overall correlated with `Estado` and 11 other fields	High correlation
`provincia` is highly overall correlated with `cant_socios` and 1 other fields	High correlation
`total_articulos_provee` is highly overall correlated with `cant_representante` and 1 other fields	High correlation
`Estado` is highly imbalanced (60.3%)	Imbalance
`TipoSocietario` is highly imbalanced (88.3%)	Imbalance
`cant_Apoderado` is highly imbalanced (84.7%)	Imbalance
`cant_representante` is highly imbalanced (75.2%)	Imbalance
`cant_autenticado` is highly imbalanced (85.9%)	Imbalance
`cant_noAutenticado` is highly imbalanced (75.9%)	Imbalance
`cant_sinMontoLimite` is highly imbalanced (82.4%)	Imbalance
`Estado` has 98 (2.5%) missing values	Missing
`TipoSocietario` has 98 (2.5%) missing values	Missing
`antiguedad` has 98 (2.5%) missing values	Missing
`cant_socios` has 3864 (99.3%) missing values	Missing
`cant_apercibimientos` has 3867 (99.4%) missing values	Missing
`cant_suspensiones` has 3858 (99.2%) missing values	Missing
`cant_antecedentes` has 3841 (98.7%) missing values	Missing
`cant_Apoderado` has 150 (3.9%) missing values	Missing
`cant_representante` has 3786 (97.3%) missing values	Missing
`cant_autenticado` has 98 (2.5%) missing values	Missing
`cant_noAutenticado` has 3779 (97.1%) missing values	Missing
`cant_sinMontoLimite` has 100 (2.6%) missing values	Missing
`cant_MontoLimite` has 3885 (99.8%) missing values	Missing
`total_articulos_provee` has 98 (2.5%) missing values	Missing
`dtotal_articulos_provee` has 98 (2.5%) missing values	Missing
`monto_total_adjudicado` is highly skewed (γ1 = 27.68665564)	Skewed
`CUIT` has unique values	Unique
`periodo_preinscripcion` has 98 (2.5%) zeros	Zeros
`antiguedad` has 702 (18.0%) zeros	Zeros

Reproduction

Analysis started	2025-06-18 13:02:51.048779
Analysis finished	2025-06-18 13:02:56.524171
Duration	5.48 seconds
Software version	ydata-profiling vv4.16.1
Download configuration	config.json

CUIT
Text

Unique

Distinct	3891
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	288.7 KiB

Length

Max length	14
Median length	11
Mean length	10.966076
Min length	3

Characters and Unicode

Total characters	42669
Distinct characters	12
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	3891 ?
Unique (%)	100.0%

Sample

1st row	27236909900
2nd row	20305924076
3rd row	20082883240
4th row	20230506060
5th row	20141208269

Value	Count	Frequency (%)
20303683489	1	< 0.1%
27331126530	1	< 0.1%
27236909900	1	< 0.1%
20305924076	1	< 0.1%
20082883240	1	< 0.1%
20230506060	1	< 0.1%
20141208269	1	< 0.1%
20271472901	1	< 0.1%
20302787221	1	< 0.1%
30546666707	1	< 0.1%
Other values (3881)	3881	99.7%

Most occurring characters

Value	Count	Frequency (%)
2	8313	19.5%
0	6019	14.1%
3	4298	10.1%
1	4147	9.7%
7	4036	9.5%
4	3354	7.9%
9	3216	7.5%
6	3151	7.4%
8	3107	7.3%
5	3025	7.1%
Other values (2)	3	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	42669	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
2	8313	19.5%
0	6019	14.1%
3	4298	10.1%
1	4147	9.7%
7	4036	9.5%
4	3354	7.9%
9	3216	7.5%
6	3151	7.4%
8	3107	7.3%
5	3025	7.1%
Other values (2)	3	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	42669	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
2	8313	19.5%
0	6019	14.1%
3	4298	10.1%
1	4147	9.7%
7	4036	9.5%
4	3354	7.9%
9	3216	7.5%
6	3151	7.4%
8	3107	7.3%
5	3025	7.1%
Other values (2)	3	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	42669	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
2	8313	19.5%
0	6019	14.1%
3	4298	10.1%
1	4147	9.7%
7	4036	9.5%
4	3354	7.9%
9	3216	7.5%
6	3151	7.4%
8	3107	7.3%
5	3025	7.1%
Other values (2)	3	< 0.1%

Nombre
Text

Distinct	2873
Distinct (%)	73.8%
Missing	0
Missing (%)	0.0%
Memory size	319.4 KiB

Length

Max length	79
Median length	57
Mean length	16.074788
Min length	1

Characters and Unicode

Total characters	62547
Distinct characters	91
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2869 ?
Unique (%)	73.7%

Sample

1st row	EMR VENTAS & SERVICIOS
2nd row	Suministros EDA
3rd row	SEGUMAX de HORACIO MIGUEL ESPOSITO
4th row	sin datos
5th row	sin datos

Value	Count	Frequency (%)
sin	1017	10.7%
datos	1016	10.6%
de	270	2.8%
servicios	103	1.1%
y	90	0.9%
la	75	0.8%
del	67	0.7%
municipalidad	62	0.6%
	50	0.5%
daniel	45	0.5%
Other values (3667)	6747	70.7%

Most occurring characters

Value	Count	Frequency (%)
	5651	9.0%
A	3923	6.3%
a	3312	5.3%
s	3110	5.0%
i	2930	4.7%
E	2869	4.6%
I	2791	4.5%
o	2657	4.2%
R	2418	3.9%
n	2366	3.8%
Other values (81)	30520	48.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	62547	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	5651	9.0%
A	3923	6.3%
a	3312	5.3%
s	3110	5.0%
i	2930	4.7%
E	2869	4.6%
I	2791	4.5%
o	2657	4.2%
R	2418	3.9%
n	2366	3.8%
Other values (81)	30520	48.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	62547	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	5651	9.0%
A	3923	6.3%
a	3312	5.3%
s	3110	5.0%
i	2930	4.7%
E	2869	4.6%
I	2791	4.5%
o	2657	4.2%
R	2418	3.9%
n	2366	3.8%
Other values (81)	30520	48.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	62547	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	5651	9.0%
A	3923	6.3%
a	3312	5.3%
s	3110	5.0%
i	2930	4.7%
E	2869	4.6%
I	2791	4.5%
o	2657	4.2%
R	2418	3.9%
n	2366	3.8%
Other values (81)	30520	48.8%

FechaPreinscripcion
Text

Distinct	1492
Distinct (%)	38.3%
Missing	0
Missing (%)	0.0%
Memory size	284.9 KiB

Length

Max length	10
Median length	10
Mean length	9.9748137
Min length	9

Characters and Unicode

Total characters	38812
Distinct characters	19
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	613 ?
Unique (%)	15.8%

Sample

1st row	04/10/2016
2nd row	13/10/2016
3rd row	18/10/2016
4th row	15/08/2016
5th row	23/09/2016

Value	Count	Frequency (%)
sin	98	2.5%
datos	98	2.5%
17/11/2021	25	0.6%
27/12/2016	13	0.3%
01/02/2017	13	0.3%
23/11/2016	12	0.3%
07/02/2017	11	0.3%
09/08/2017	11	0.3%
26/12/2016	11	0.3%
10/04/2017	11	0.3%
Other values (1483)	3686	92.4%

Most occurring characters

Value	Count	Frequency (%)
0	8746	22.5%
/	7586	19.5%
2	7301	18.8%
1	6421	16.5%
7	1912	4.9%
8	1418	3.7%
9	1112	2.9%
6	1094	2.8%
3	917	2.4%
5	744	1.9%
Other values (9)	1561	4.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	38812	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	8746	22.5%
/	7586	19.5%
2	7301	18.8%
1	6421	16.5%
7	1912	4.9%
8	1418	3.7%
9	1112	2.9%
6	1094	2.8%
3	917	2.4%
5	744	1.9%
Other values (9)	1561	4.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	38812	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	8746	22.5%
/	7586	19.5%
2	7301	18.8%
1	6421	16.5%
7	1912	4.9%
8	1418	3.7%
9	1112	2.9%
6	1094	2.8%
3	917	2.4%
5	744	1.9%
Other values (9)	1561	4.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	38812	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	8746	22.5%
/	7586	19.5%
2	7301	18.8%
1	6421	16.5%
7	1912	4.9%
8	1418	3.7%
9	1112	2.9%
6	1094	2.8%
3	917	2.4%
5	744	1.9%
Other values (9)	1561	4.0%

Estado
Categorical

High correlation Imbalance Missing

Distinct	8
Distinct (%)	0.2%
Missing	98
Missing (%)	2.5%
Memory size	292.6 KiB

Inscripto	2919
Pre Inscripto	446
Desactualizado Por Documentos Vencidos	272
Con Solicitud De Baja	55
Desactualizado Por Mantencion Formulario	54
Other values (3)	47

Length

Max length	40
Median length	9
Mean length	12.330082
Min length	9

Characters and Unicode

Total characters	46768
Distinct characters	28
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	Inscripto
2nd row	Inscripto
3rd row	Desactualizado Por Documentos Vencidos
4th row	Inscripto
5th row	Inscripto

Common Values

Value	Count	Frequency (%)
Inscripto	2919	75.0%
Pre Inscripto	446	11.5%
Desactualizado Por Documentos Vencidos	272	7.0%
Con Solicitud De Baja	55	1.4%
Desactualizado Por Mantencion Formulario	54	1.4%
Desactualizado Por Clase	40	1.0%
En Evaluacion	6	0.2%
Suspendido	1	< 0.1%
(Missing)	98	2.5%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
inscripto	3365	61.5%
pre	446	8.2%
desactualizado	366	6.7%
por	366	6.7%
documentos	272	5.0%
vencidos	272	5.0%
con	55	1.0%
solicitud	55	1.0%
de	55	1.0%
baja	55	1.0%
Other values (6)	161	2.9%

Most occurring characters

Value	Count	Frequency (%)
o	5192	11.1%
c	4390	9.4%
s	4316	9.2%
r	4285	9.2%
i	4228	9.0%
n	4139	8.9%
t	4112	8.8%
p	3366	7.2%
I	3365	7.2%
	1675	3.6%
Other values (18)	7700	16.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	46768	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
o	5192	11.1%
c	4390	9.4%
s	4316	9.2%
r	4285	9.2%
i	4228	9.0%
n	4139	8.9%
t	4112	8.8%
p	3366	7.2%
I	3365	7.2%
	1675	3.6%
Other values (18)	7700	16.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	46768	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
o	5192	11.1%
c	4390	9.4%
s	4316	9.2%
r	4285	9.2%
i	4228	9.0%
n	4139	8.9%
t	4112	8.8%
p	3366	7.2%
I	3365	7.2%
	1675	3.6%
Other values (18)	7700	16.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	46768	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
o	5192	11.1%
c	4390	9.4%
s	4316	9.2%
r	4285	9.2%
i	4228	9.0%
n	4139	8.9%
t	4112	8.8%
p	3366	7.2%
I	3365	7.2%
	1675	3.6%
Other values (18)	7700	16.5%

TipoSocietario
Categorical

High correlation Imbalance Missing

Distinct	6
Distinct (%)	0.2%
Missing	98
Missing (%)	2.5%
Memory size	441.6 KiB

Persona Física	3622
Organismo Publico	144
Sociedad Anónima	21
Otras Formas Societarias	2
Sociedades De Hecho	2

Length

Max length	24
Median length	14
Mean length	14.131822
Min length	12

Characters and Unicode

Total characters	53602
Distinct characters	29
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Persona Física
2nd row	Persona Física
3rd row	Persona Física
4th row	Persona Física
5th row	Persona Física

Common Values

Value	Count	Frequency (%)
Persona Física	3622	93.1%
Organismo Publico	144	3.7%
Sociedad Anónima	21	0.5%
Otras Formas Societarias	2	0.1%
Sociedades De Hecho	2	0.1%
Cooperativas	2	0.1%
(Missing)	98	2.5%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
persona	3622	47.7%
física	3622	47.7%
organismo	144	1.9%
publico	144	1.9%
sociedad	21	0.3%
anónima	21	0.3%
otras	2	< 0.1%
formas	2	< 0.1%
societarias	2	< 0.1%
sociedades	2	< 0.1%
Other values (3)	6	0.1%

Most occurring characters

Value	Count	Frequency (%)
a	7444	13.9%
s	7398	13.8%
i	3960	7.4%
o	3943	7.4%
n	3808	7.1%
	3795	7.1%
c	3793	7.1%
r	3774	7.0%
P	3766	7.0%
e	3655	6.8%
Other values (19)	8266	15.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	53602	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	7444	13.9%
s	7398	13.8%
i	3960	7.4%
o	3943	7.4%
n	3808	7.1%
	3795	7.1%
c	3793	7.1%
r	3774	7.0%
P	3766	7.0%
e	3655	6.8%
Other values (19)	8266	15.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	53602	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	7444	13.9%
s	7398	13.8%
i	3960	7.4%
o	3943	7.4%
n	3808	7.1%
	3795	7.1%
c	3793	7.1%
r	3774	7.0%
P	3766	7.0%
e	3655	6.8%
Other values (19)	8266	15.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	53602	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	7444	13.9%
s	7398	13.8%
i	3960	7.4%
o	3943	7.4%
n	3808	7.1%
	3795	7.1%
c	3793	7.1%
r	3774	7.0%
P	3766	7.0%
e	3655	6.8%
Other values (19)	8266	15.4%

periodo_preinscripcion
Real number (ℝ)

High correlation Zeros

Distinct	79
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	196767.38

Minimum	0
Maximum	202303
Zeros	98
Zeros (%)	2.5%
Negative	0
Negative (%)	0.0%
Memory size	60.8 KiB

Quantile statistics

Minimum	0
5-th percentile	201610
Q1	201705
median	201805
Q3	202005
95-th percentile	202203
Maximum	202303
Range	202303
Interquartile range (IQR)	300

Descriptive statistics

Standard deviation	31632.764
Coefficient of variation (CV)	0.16076224
Kurtosis	34.773837
Mean	196767.38
Median Absolute Deviation (MAD)	102
Skewness	-6.0625672
Sum	7.6562186 × 10⁸
Variance	1.0006317 × 10⁹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
201705	128	3.3%
201611	126	3.2%
201706	120	3.1%
201703	114	2.9%
201612	113	2.9%
201704	109	2.8%
201702	108	2.8%
201708	107	2.7%
201701	107	2.7%
0	98	2.5%
Other values (69)	2761	71.0%

Value	Count	Frequency (%)
0	98	2.5%
201607	11	0.3%
201608	24	0.6%
201609	23	0.6%
201610	51	1.3%
201611	126	3.2%
201612	113	2.9%
201701	107	2.7%
201702	108	2.8%
201703	114	2.9%

Value	Count	Frequency (%)
202303	1	< 0.1%
202211	6	0.2%
202210	10	0.3%
202209	28	0.7%
202208	32	0.8%
202207	19	0.5%
202206	26	0.7%
202205	34	0.9%
202204	31	0.8%
202203	29	0.7%

anio_preinscripcion
Categorical

High correlation

Distinct	9
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	262.7 KiB

2017	1189
2018	711
2019	468
2021	443
2020	375
Other values (4)	705

Length

Max length	9
Median length	4
Mean length	4.1259316
Min length	4

Characters and Unicode

Total characters	16054
Distinct characters	16
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	2016
2nd row	2016
3rd row	2016
4th row	2016
5th row	2016

Common Values

Value	Count	Frequency (%)
2017	1189	30.6%
2018	711	18.3%
2019	468	12.0%
2021	443	11.4%
2020	375	9.6%
2016	348	8.9%
2022	258	6.6%
sin datos	98	2.5%
2023	1	< 0.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
2017	1189	29.8%
2018	711	17.8%
2019	468	11.7%
2021	443	11.1%
2020	375	9.4%
2016	348	8.7%
2022	258	6.5%
sin	98	2.5%
datos	98	2.5%
2023	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
2	5128	31.9%
0	4168	26.0%
1	3159	19.7%
7	1189	7.4%
8	711	4.4%
9	468	2.9%
6	348	2.2%
s	196	1.2%
i	98	0.6%
n	98	0.6%
Other values (6)	491	3.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	16054	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
2	5128	31.9%
0	4168	26.0%
1	3159	19.7%
7	1189	7.4%
8	711	4.4%
9	468	2.9%
6	348	2.2%
s	196	1.2%
i	98	0.6%
n	98	0.6%
Other values (6)	491	3.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	16054	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
2	5128	31.9%
0	4168	26.0%
1	3159	19.7%
7	1189	7.4%
8	711	4.4%
9	468	2.9%
6	348	2.2%
s	196	1.2%
i	98	0.6%
n	98	0.6%
Other values (6)	491	3.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	16054	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
2	5128	31.9%
0	4168	26.0%
1	3159	19.7%
7	1189	7.4%
8	711	4.4%
9	468	2.9%
6	348	2.2%
s	196	1.2%
i	98	0.6%
n	98	0.6%
Other values (6)	491	3.1%

cant_procesos_adjudicado
Real number (ℝ)

High correlation

Distinct	138
Distinct (%)	3.6%
Missing	6
Missing (%)	0.2%
Infinite	0
Infinite (%)	0.0%
Mean	9.1660232

Minimum	1
Maximum	895
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	60.8 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	2
Q3	4
95-th percentile	31
Maximum	895
Range	894
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	41.114995
Coefficient of variation (CV)	4.4855871
Kurtosis	217.13381
Mean	9.1660232
Median Absolute Deviation (MAD)	1
Skewness	12.885379
Sum	35610
Variance	1690.4428
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	1728	44.4%
2	715	18.4%
3	366	9.4%
4	209	5.4%
5	126	3.2%
6	102	2.6%
7	63	1.6%
8	47	1.2%
9	43	1.1%
11	40	1.0%
Other values (128)	446	11.5%

Value	Count	Frequency (%)
1	1728	44.4%
2	715	18.4%
3	366	9.4%
4	209	5.4%
5	126	3.2%
6	102	2.6%
7	63	1.6%
8	47	1.2%
9	43	1.1%
10	32	0.8%

Value	Count	Frequency (%)
895	1	< 0.1%
889	1	< 0.1%
804	1	< 0.1%
792	1	< 0.1%
635	1	< 0.1%
525	1	< 0.1%
438	1	< 0.1%
409	1	< 0.1%
382	1	< 0.1%
379	1	< 0.1%

monto_total_adjudicado
Real number (ℝ)

High correlation Skewed

Distinct	3715
Distinct (%)	95.6%
Missing	6
Missing (%)	0.2%
Infinite	0
Infinite (%)	0.0%
Mean	15961656

Minimum	0
Maximum	5.0920925 × 10⁹
Zeros	35
Zeros (%)	0.9%
Negative	0
Negative (%)	0.0%
Memory size	60.8 KiB

Quantile statistics

Minimum	0
5-th percentile	34459.459
Q1	376952.96
median	1645642.5
Q3	6710526.3
95-th percentile	50904056
Maximum	5.0920925 × 10⁹
Range	5.0920925 × 10⁹
Interquartile range (IQR)	6333573.4

Descriptive statistics

Standard deviation	1.2177206 × 10⁸
Coefficient of variation (CV)	7.6290368
Kurtosis	966.17605
Mean	15961656
Median Absolute Deviation (MAD)	1518142.5
Skewness	27.686656
Sum	6.2011034 × 10¹⁰
Variance	1.4828435 × 10¹⁶
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	35	0.9%
6710526.316	7	0.2%
85000	4	0.1%
40800	4	0.1%
114750	4	0.1%
526451.6129	4	0.1%
240428.5714	4	0.1%
255000	4	0.1%
21857.14286	4	0.1%
49038.46154	3	0.1%
Other values (3705)	3812	98.0%
(Missing)	6	0.2%

Value	Count	Frequency (%)
0	35	0.9%
0.010851064	1	< 0.1%
0.056666667	1	< 0.1%
0.80952381	1	< 0.1%
1.65952381	1	< 0.1%
2.487804878	2	0.1%
12.648	1	< 0.1%
36.13714286	1	< 0.1%
120.2142857	1	< 0.1%
154.1027027	1	< 0.1%

Value	Count	Frequency (%)
5092092510	1	< 0.1%
3205078998	1	< 0.1%
2525171710	1	< 0.1%
1624050032	1	< 0.1%
1501157408	1	< 0.1%
1386549515	1	< 0.1%
1129301338	1	< 0.1%
1023647402	1	< 0.1%
1006323598	1	< 0.1%
778852664.9	1	< 0.1%

antiguedad
Real number (ℝ)

High correlation Missing Zeros

Distinct	6
Distinct (%)	0.2%
Missing	98
Missing (%)	2.5%
Infinite	0
Infinite (%)	0.0%
Mean	2.6206169

Minimum	0
Maximum	5
Zeros	702
Zeros (%)	18.0%
Negative	0
Negative (%)	0.0%
Memory size	60.8 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1
median	3
Q3	4
95-th percentile	5
Maximum	5
Range	5
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	1.649788
Coefficient of variation (CV)	0.62954185
Kurtosis	-1.1755102
Mean	2.6206169
Median Absolute Deviation (MAD)	1
Skewness	-0.38163944
Sum	9940
Variance	2.7218006
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
4	1189	30.6%
3	711	18.3%
0	702	18.0%
2	468	12.0%
1	375	9.6%
5	348	8.9%
(Missing)	98	2.5%

Value	Count	Frequency (%)
0	702	18.0%
1	375	9.6%
2	468	12.0%
3	711	18.3%
4	1189	30.6%
5	348	8.9%

Value	Count	Frequency (%)
5	348	8.9%
4	1189	30.6%
3	711	18.3%
2	468	12.0%
1	375	9.6%
0	702	18.0%

provincia
Categorical

High correlation

Distinct	27
Distinct (%)	0.7%
Missing	0
Missing (%)	0.0%
Memory size	357.8 KiB

Buenos Aires	1139
Ciudad Autónoma de Buenos Aires	809
Córdoba	255
Santa Fe	142
Chubut	133
Other values (22)	1413

Length

Max length	31
Median length	19
Mean length	14.013878
Min length	1

Characters and Unicode

Total characters	54528
Distinct characters	40
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	0.1%

Sample

1st row	Chubut
2nd row	Ciudad Autónoma de Buenos Aires
3rd row	Ciudad Autónoma de Buenos Aires
4th row	Ciudad Autónoma de Buenos Aires
5th row	Ciudad Autónoma de Buenos Aires

Common Values

Value	Count	Frequency (%)
Buenos Aires	1139	29.3%
Ciudad Autónoma de Buenos Aires	809	20.8%
Córdoba	255	6.6%
Santa Fe	142	3.6%
Chubut	133	3.4%
Mendoza	128	3.3%
sin datos	115	3.0%
Misiones	112	2.9%
Rio Negro	111	2.9%
Entre Rios	91	2.3%
Other values (17)	856	22.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
buenos	1948	21.2%
aires	1948	21.2%
ciudad	809	8.8%
autónoma	809	8.8%
de	809	8.8%
córdoba	255	2.8%
santa	210	2.3%
fe	142	1.5%
chubut	133	1.4%
mendoza	128	1.4%
Other values (28)	1990	21.7%

Most occurring characters

Value	Count	Frequency (%)
e	5776	10.6%
	5290	9.7%
s	4656	8.5%
u	4410	8.1%
o	4147	7.6%
n	3784	6.9%
i	3545	6.5%
a	3486	6.4%
d	3033	5.6%
r	2877	5.3%
Other values (30)	13524	24.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	54528	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	5776	10.6%
	5290	9.7%
s	4656	8.5%
u	4410	8.1%
o	4147	7.6%
n	3784	6.9%
i	3545	6.5%
a	3486	6.4%
d	3033	5.6%
r	2877	5.3%
Other values (30)	13524	24.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	54528	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	5776	10.6%
	5290	9.7%
s	4656	8.5%
u	4410	8.1%
o	4147	7.6%
n	3784	6.9%
i	3545	6.5%
a	3486	6.4%
d	3033	5.6%
r	2877	5.3%
Other values (30)	13524	24.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	54528	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	5776	10.6%
	5290	9.7%
s	4656	8.5%
u	4410	8.1%
o	4147	7.6%
n	3784	6.9%
i	3545	6.5%
a	3486	6.4%
d	3033	5.6%
r	2877	5.3%
Other values (30)	13524	24.8%

cant_socios
Categorical

High correlation Missing

Distinct	5
Distinct (%)	18.5%
Missing	3864
Missing (%)	99.3%
Memory size	243.3 KiB

1.0	12
2.0	10
3.0	2
4.0	2
16.0	1

Length

Max length	4
Median length	3
Mean length	3.037037
Min length	3

Characters and Unicode

Total characters	82
Distinct characters	7
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	3.7%

Sample

1st row	2.0
2nd row	2.0
3rd row	16.0
4th row	1.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
1.0	12	0.3%
2.0	10	0.3%
3.0	2	0.1%
4.0	2	0.1%
16.0	1	< 0.1%
(Missing)	3864	99.3%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1.0	12	44.4%
2.0	10	37.0%
3.0	2	7.4%
4.0	2	7.4%
16.0	1	3.7%

Most occurring characters

Value	Count	Frequency (%)
.	27	32.9%
0	27	32.9%
1	13	15.9%
2	10	12.2%
3	2	2.4%
4	2	2.4%
6	1	1.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	82	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
.	27	32.9%
0	27	32.9%
1	13	15.9%
2	10	12.2%
3	2	2.4%
4	2	2.4%
6	1	1.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	82	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
.	27	32.9%
0	27	32.9%
1	13	15.9%
2	10	12.2%
3	2	2.4%
4	2	2.4%
6	1	1.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	82	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
.	27	32.9%
0	27	32.9%
1	13	15.9%
2	10	12.2%
3	2	2.4%
4	2	2.4%
6	1	1.2%

cant_apercibimientos
Categorical

Constant Missing

Distinct	1
Distinct (%)	4.2%
Missing	3867
Missing (%)	99.4%
Memory size	243.3 KiB

1.0	24

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	72
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	24	0.6%
(Missing)	3867	99.4%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1.0	24	100.0%

Most occurring characters

Value	Count	Frequency (%)
1	24	33.3%
.	24	33.3%
0	24	33.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	72	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
1	24	33.3%
.	24	33.3%
0	24	33.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	72	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
1	24	33.3%
.	24	33.3%
0	24	33.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	72	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
1	24	33.3%
.	24	33.3%
0	24	33.3%

cant_suspensiones
Real number (ℝ)

High correlation Missing

Distinct	6
Distinct (%)	18.2%
Missing	3858
Missing (%)	99.2%
Infinite	0
Infinite (%)	0.0%
Mean	2.2121212

Minimum	1
Maximum	7
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	60.8 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	2
Q3	2
95-th percentile	6
Maximum	7
Range	6
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.5361798
Coefficient of variation (CV)	0.69443746
Kurtosis	3.3438087
Mean	2.2121212
Median Absolute Deviation (MAD)	1
Skewness	1.9328412
Sum	73
Variance	2.3598485
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
2	16	0.4%
1	11	0.3%
6	2	0.1%
4	2	0.1%
3	1	< 0.1%
7	1	< 0.1%
(Missing)	3858	99.2%

Value	Count	Frequency (%)
1	11	0.3%
2	16	0.4%
3	1	< 0.1%
4	2	0.1%
6	2	0.1%
7	1	< 0.1%

Value	Count	Frequency (%)
7	1	< 0.1%
6	2	0.1%
4	2	0.1%
3	1	< 0.1%
2	16	0.4%
1	11	0.3%

cant_antecedentes
Real number (ℝ)

High correlation Missing

Distinct	8
Distinct (%)	16.0%
Missing	3841
Missing (%)	98.7%
Infinite	0
Infinite (%)	0.0%
Mean	2.08

Minimum	1
Maximum	8
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	60.8 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	2
Q3	2
95-th percentile	5.55
Maximum	8
Range	7
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.5231546
Coefficient of variation (CV)	0.73228588
Kurtosis	6.1363264
Mean	2.08
Median Absolute Deviation (MAD)	1
Skewness	2.4225506
Sum	104
Variance	2.32
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=8)

Value	Count	Frequency (%)
2	24	0.6%
1	19	0.5%
4	2	0.1%
7	1	< 0.1%
5	1	< 0.1%
3	1	< 0.1%
6	1	< 0.1%
8	1	< 0.1%
(Missing)	3841	98.7%

Value	Count	Frequency (%)
1	19	0.5%
2	24	0.6%
3	1	< 0.1%
4	2	0.1%
5	1	< 0.1%
6	1	< 0.1%
7	1	< 0.1%
8	1	< 0.1%

Value	Count	Frequency (%)
8	1	< 0.1%
7	1	< 0.1%
6	1	< 0.1%
5	1	< 0.1%
4	2	0.1%
3	1	< 0.1%
2	24	0.6%
1	19	0.5%

cant_Apoderado
Categorical

High correlation Imbalance Missing

Distinct	5
Distinct (%)	0.1%
Missing	150
Missing (%)	3.9%
Memory size	257.8 KiB

1.0	3516
2.0	208
3.0	14
4.0	2
10.0	1

Length

Max length	4
Median length	3
Mean length	3.0002673
Min length	3

Characters and Unicode

Total characters	11224
Distinct characters	6
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	1.0
2nd row	2.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	3516	90.4%
2.0	208	5.3%
3.0	14	0.4%
4.0	2	0.1%
10.0	1	< 0.1%
(Missing)	150	3.9%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1.0	3516	94.0%
2.0	208	5.6%
3.0	14	0.4%
4.0	2	0.1%
10.0	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
0	3742	33.3%
.	3741	33.3%
1	3517	31.3%
2	208	1.9%
3	14	0.1%
4	2	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	11224	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	3742	33.3%
.	3741	33.3%
1	3517	31.3%
2	208	1.9%
3	14	0.1%
4	2	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	11224	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	3742	33.3%
.	3741	33.3%
1	3517	31.3%
2	208	1.9%
3	14	0.1%
4	2	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	11224	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	3742	33.3%
.	3741	33.3%
1	3517	31.3%
2	208	1.9%
3	14	0.1%
4	2	< 0.1%

cant_representante
Categorical

High correlation Imbalance Missing

Distinct	3
Distinct (%)	2.9%
Missing	3786
Missing (%)	97.3%
Memory size	243.6 KiB

1.0	98
2.0	6
4.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	315
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	1.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	98	2.5%
2.0	6	0.2%
4.0	1	< 0.1%
(Missing)	3786	97.3%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1.0	98	93.3%
2.0	6	5.7%
4.0	1	1.0%

Most occurring characters

Value	Count	Frequency (%)
.	105	33.3%
0	105	33.3%
1	98	31.1%
2	6	1.9%
4	1	0.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	315	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
.	105	33.3%
0	105	33.3%
1	98	31.1%
2	6	1.9%
4	1	0.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	315	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
.	105	33.3%
0	105	33.3%
1	98	31.1%
2	6	1.9%
4	1	0.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	315	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
.	105	33.3%
0	105	33.3%
1	98	31.1%
2	6	1.9%
4	1	0.3%

cant_autenticado
Categorical

High correlation Imbalance Missing

Distinct	4
Distinct (%)	0.1%
Missing	98
Missing (%)	2.5%
Memory size	258.0 KiB

1.0	3622
2.0	159
3.0	11
4.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	11379
Distinct characters	6
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	3622	93.1%
2.0	159	4.1%
3.0	11	0.3%
4.0	1	< 0.1%
(Missing)	98	2.5%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1.0	3622	95.5%
2.0	159	4.2%
3.0	11	0.3%
4.0	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
.	3793	33.3%
0	3793	33.3%
1	3622	31.8%
2	159	1.4%
3	11	0.1%
4	1	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	11379	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
.	3793	33.3%
0	3793	33.3%
1	3622	31.8%
2	159	1.4%
3	11	0.1%
4	1	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	11379	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
.	3793	33.3%
0	3793	33.3%
1	3622	31.8%
2	159	1.4%
3	11	0.1%
4	1	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	11379	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
.	3793	33.3%
0	3793	33.3%
1	3622	31.8%
2	159	1.4%
3	11	0.1%
4	1	< 0.1%

cant_noAutenticado
Categorical

High correlation Imbalance Missing

Distinct	4
Distinct (%)	3.6%
Missing	3779
Missing (%)	97.1%
Memory size	243.6 KiB

1.0	103
2.0	7
3.0	1
9.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	336
Distinct characters	6
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	1.8%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	103	2.6%
2.0	7	0.2%
3.0	1	< 0.1%
9.0	1	< 0.1%
(Missing)	3779	97.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1.0	103	92.0%
2.0	7	6.2%
3.0	1	0.9%
9.0	1	0.9%

Most occurring characters

Value	Count	Frequency (%)
.	112	33.3%
0	112	33.3%
1	103	30.7%
2	7	2.1%
3	1	0.3%
9	1	0.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	336	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
.	112	33.3%
0	112	33.3%
1	103	30.7%
2	7	2.1%
3	1	0.3%
9	1	0.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	336	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
.	112	33.3%
0	112	33.3%
1	103	30.7%
2	7	2.1%
3	1	0.3%
9	1	0.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	336	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
.	112	33.3%
0	112	33.3%
1	103	30.7%
2	7	2.1%
3	1	0.3%
9	1	0.3%

cant_sinMontoLimite
Categorical

High correlation Imbalance Missing

Distinct	5
Distinct (%)	0.1%
Missing	100
Missing (%)	2.6%
Memory size	258.0 KiB

1.0	3517
2.0	251
3.0	19
4.0	3
12.0	1

Length

Max length	4
Median length	3
Mean length	3.0002638
Min length	3

Characters and Unicode

Total characters	11374
Distinct characters	6
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	1.0
2nd row	2.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	3517	90.4%
2.0	251	6.5%
3.0	19	0.5%
4.0	3	0.1%
12.0	1	< 0.1%
(Missing)	100	2.6%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1.0	3517	92.8%
2.0	251	6.6%
3.0	19	0.5%
4.0	3	0.1%
12.0	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
.	3791	33.3%
0	3791	33.3%
1	3518	30.9%
2	252	2.2%
3	19	0.2%
4	3	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	11374	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
.	3791	33.3%
0	3791	33.3%
1	3518	30.9%
2	252	2.2%
3	19	0.2%
4	3	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	11374	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
.	3791	33.3%
0	3791	33.3%
1	3518	30.9%
2	252	2.2%
3	19	0.2%
4	3	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	11374	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
.	3791	33.3%
0	3791	33.3%
1	3518	30.9%
2	252	2.2%
3	19	0.2%
4	3	< 0.1%

cant_MontoLimite
Categorical

Constant Missing

Distinct	1
Distinct (%)	16.7%
Missing	3885
Missing (%)	99.8%
Memory size	243.2 KiB

1.0	6

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	18
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	6	0.2%
(Missing)	3885	99.8%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1.0	6	100.0%

Most occurring characters

Value	Count	Frequency (%)
1	6	33.3%
.	6	33.3%
0	6	33.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	18	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
1	6	33.3%
.	6	33.3%
0	6	33.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	18	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
1	6	33.3%
.	6	33.3%
0	6	33.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	18	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
1	6	33.3%
.	6	33.3%
0	6	33.3%

total_articulos_provee
Real number (ℝ)

High correlation Missing

Distinct	477
Distinct (%)	12.6%
Missing	98
Missing (%)	2.5%
Infinite	0
Infinite (%)	0.0%
Mean	78.913525

Minimum	1
Maximum	6993
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	60.8 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	5
Q3	37
95-th percentile	437.8
Maximum	6993
Range	6992
Interquartile range (IQR)	36

Descriptive statistics

Standard deviation	287.25365
Coefficient of variation (CV)	3.6401067
Kurtosis	245.11641
Mean	78.913525
Median Absolute Deviation (MAD)	4
Skewness	12.889009
Sum	299319
Variance	82514.66
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	1266	32.5%
2	302	7.8%
3	180	4.6%
4	125	3.2%
5	122	3.1%
6	86	2.2%
7	65	1.7%
8	64	1.6%
9	56	1.4%
11	48	1.2%
Other values (467)	1479	38.0%
(Missing)	98	2.5%

Value	Count	Frequency (%)
1	1266	32.5%
2	302	7.8%
3	180	4.6%
4	125	3.2%
5	122	3.1%
6	86	2.2%
7	65	1.7%
8	64	1.6%
9	56	1.4%
10	40	1.0%

Value	Count	Frequency (%)
6993	1	< 0.1%
6661	1	< 0.1%
5612	1	< 0.1%
4867	1	< 0.1%
4471	1	< 0.1%
3956	1	< 0.1%
2868	1	< 0.1%
1922	1	< 0.1%
1742	1	< 0.1%
1732	1	< 0.1%

dmonto_total_adjudicado
Categorical

High correlation

Distinct	20
Distinct (%)	0.5%
Missing	6
Missing (%)	0.2%
Memory size	339.1 KiB

(1302657.558, 1793326.755]	282
(377939.298, 599760.0]	268
(104767.373, 224078.198]	268
(33011.111, 104767.373]	261
(224078.198, 377939.298]	258
Other values (15)	2548

Length

Max length	29
Median length	28
Mean length	24.267439
Min length	19

Characters and Unicode

Total characters	94279
Distinct characters	16
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	(9424898.401, 13557176.81]
2nd row	(89439449.702, 222964579.98]
3rd row	(890758.9, 1302657.558]
4th row	(89439449.702, 222964579.98]
5th row	(599760.0, 890758.9]

Common Values

Value	Count	Frequency (%)
(1302657.558, 1793326.755]	282	7.2%
(377939.298, 599760.0]	268	6.9%
(104767.373, 224078.198]	268	6.9%
(33011.111, 104767.373]	261	6.7%
(224078.198, 377939.298]	258	6.6%
(890758.9, 1302657.558]	249	6.4%
(1793326.755, 2483085.385]	242	6.2%
(599760.0, 890758.9]	240	6.2%
(2483085.385, 3396600.0]	238	6.1%
(3396600.0, 4727330.113]	206	5.3%
Other values (10)	1373	35.3%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
1302657.558	531	6.8%
104767.373	529	6.8%
377939.298	526	6.8%
224078.198	526	6.8%
1793326.755	524	6.7%
599760.0	508	6.5%
890758.9	489	6.3%
2483085.385	480	6.2%
33011.111	447	5.8%
3396600.0	444	5.7%
Other values (11)	2766	35.6%

Most occurring characters

Value	Count	Frequency (%)
7	9219	9.8%
3	8706	9.2%
1	8284	8.8%
9	7933	8.4%
.	7770	8.2%
0	7587	8.0%
8	7585	8.0%
5	7027	7.5%
2	5152	5.5%
6	4909	5.2%
Other values (6)	20107	21.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	94279	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
7	9219	9.8%
3	8706	9.2%
1	8284	8.8%
9	7933	8.4%
.	7770	8.2%
0	7587	8.0%
8	7585	8.0%
5	7027	7.5%
2	5152	5.5%
6	4909	5.2%
Other values (6)	20107	21.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	94279	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
7	9219	9.8%
3	8706	9.2%
1	8284	8.8%
9	7933	8.4%
.	7770	8.2%
0	7587	8.0%
8	7585	8.0%
5	7027	7.5%
2	5152	5.5%
6	4909	5.2%
Other values (6)	20107	21.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	94279	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
7	9219	9.8%
3	8706	9.2%
1	8284	8.8%
9	7933	8.4%
.	7770	8.2%
0	7587	8.0%
8	7585	8.0%
5	7027	7.5%
2	5152	5.5%
6	4909	5.2%
Other values (6)	20107	21.3%

dcant_procesos_adjudicado
Categorical

Distinct	10
Distinct (%)	0.3%
Missing	6
Missing (%)	0.2%
Memory size	290.9 KiB

(0.999, 2.0]	2443
(2.0, 3.0]	366
(3.0, 4.0]	209
(39.0, 1214.0]	157
(8.0, 12.0]	139
Other values (5)	571

Length

Max length	14
Median length	12
Mean length	11.575032
Min length	10

Characters and Unicode

Total characters	44969
Distinct characters	14
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	(39.0, 1214.0]
2nd row	(39.0, 1214.0]
3rd row	(0.999, 2.0]
4th row	(8.0, 12.0]
5th row	(0.999, 2.0]

Common Values

Value	Count	Frequency (%)
(0.999, 2.0]	2443	62.8%
(2.0, 3.0]	366	9.4%
(3.0, 4.0]	209	5.4%
(39.0, 1214.0]	157	4.0%
(8.0, 12.0]	139	3.6%
(4.0, 5.0]	126	3.2%
(19.0, 39.0]	120	3.1%
(12.0, 19.0]	113	2.9%
(6.0, 8.0]	110	2.8%
(5.0, 6.0]	102	2.6%
(Missing)	6	0.2%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
2.0	2809	36.2%
0.999	2443	31.4%
3.0	575	7.4%
4.0	335	4.3%
39.0	277	3.6%
12.0	252	3.2%
8.0	249	3.2%
19.0	233	3.0%
5.0	228	2.9%
6.0	212	2.7%

Most occurring characters

Value	Count	Frequency (%)
9	7839	17.4%
0	7770	17.3%
.	7770	17.3%
(	3885	8.6%
,	3885	8.6%
	3885	8.6%
]	3885	8.6%
2	3218	7.2%
3	852	1.9%
1	799	1.8%
Other values (4)	1181	2.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	44969	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
9	7839	17.4%
0	7770	17.3%
.	7770	17.3%
(	3885	8.6%
,	3885	8.6%
	3885	8.6%
]	3885	8.6%
2	3218	7.2%
3	852	1.9%
1	799	1.8%
Other values (4)	1181	2.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	44969	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
9	7839	17.4%
0	7770	17.3%
.	7770	17.3%
(	3885	8.6%
,	3885	8.6%
	3885	8.6%
]	3885	8.6%
2	3218	7.2%
3	852	1.9%
1	799	1.8%
Other values (4)	1181	2.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	44969	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
9	7839	17.4%
0	7770	17.3%
.	7770	17.3%
(	3885	8.6%
,	3885	8.6%
	3885	8.6%
]	3885	8.6%
2	3218	7.2%
3	852	1.9%
1	799	1.8%
Other values (4)	1181	2.6%

dtotal_articulos_provee
Categorical

High correlation Missing

Distinct	15
Distinct (%)	0.4%
Missing	98
Missing (%)	2.5%
Memory size	291.2 KiB

(0.999, 2.0]	1568
(345.0, 6993.0]	243
(4.0, 6.0]	208
(161.0, 345.0]	187
(2.0, 3.0]	180
Other values (10)	1407

Length

Max length	15
Median length	12
Mean length	11.96019
Min length	10

Characters and Unicode

Total characters	45365
Distinct characters	15
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	(58.0, 97.6]
2nd row	(97.6, 161.0]
3rd row	(161.0, 345.0]
4th row	(4.0, 6.0]
5th row	(15.0, 21.0]

Common Values

Value	Count	Frequency (%)
(0.999, 2.0]	1568	40.3%
(345.0, 6993.0]	243	6.2%
(4.0, 6.0]	208	5.3%
(161.0, 345.0]	187	4.8%
(2.0, 3.0]	180	4.6%
(97.6, 161.0]	174	4.5%
(58.0, 97.6]	154	4.0%
(8.0, 11.0]	144	3.7%
(40.0, 58.0]	144	3.7%
(15.0, 21.0]	139	3.6%
Other values (5)	652	16.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
2.0	1748	23.0%
0.999	1568	20.7%
345.0	430	5.7%
161.0	361	4.8%
6.0	337	4.4%
4.0	333	4.4%
97.6	328	4.3%
3.0	305	4.0%
58.0	298	3.9%
40.0	278	3.7%
Other values (6)	1600	21.1%

Most occurring characters

Value	Count	Frequency (%)
.	7586	16.7%
0	7536	16.6%
9	5786	12.8%
(	3793	8.4%
,	3793	8.4%
	3793	8.4%
]	3793	8.4%
2	2289	5.0%
1	1812	4.0%
6	1269	2.8%
Other values (5)	3915	8.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	45365	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
.	7586	16.7%
0	7536	16.6%
9	5786	12.8%
(	3793	8.4%
,	3793	8.4%
	3793	8.4%
]	3793	8.4%
2	2289	5.0%
1	1812	4.0%
6	1269	2.8%
Other values (5)	3915	8.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	45365	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
.	7586	16.7%
0	7536	16.6%
9	5786	12.8%
(	3793	8.4%
,	3793	8.4%
	3793	8.4%
]	3793	8.4%
2	2289	5.0%
1	1812	4.0%
6	1269	2.8%
Other values (5)	3915	8.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	45365	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
.	7586	16.7%
0	7536	16.6%
9	5786	12.8%
(	3793	8.4%
,	3793	8.4%
	3793	8.4%
]	3793	8.4%
2	2289	5.0%
1	1812	4.0%
6	1269	2.8%
Other values (5)	3915	8.6%

cluster_k_4
Categorical

Constant

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	250.8 KiB

1	3891

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	3891
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	3891	100.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1	3891	100.0%

Most occurring characters

Value	Count	Frequency (%)
1	3891	100.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	3891	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
1	3891	100.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	3891	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
1	3891	100.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	3891	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
1	3891	100.0%

Interactions

Correlations

	Estado	TipoSocietario	anio_preinscripcion	antiguedad	cant_Apoderado	cant_antecedentes	cant_autenticado	cant_noAutenticado	cant_procesos_adjudicado	cant_representante	cant_sinMontoLimite	cant_socios	cant_suspensiones	dcant_procesos_adjudicado	dmonto_total_adjudicado	dtotal_articulos_provee	monto_total_adjudicado	periodo_preinscripcion	provincia	total_articulos_provee
Estado	1.000	0.126	0.119	0.136	0.096	0.000	0.121	0.240	0.000	0.263	0.099	0.216	0.000	0.108	0.125	0.143	0.035	1.000	0.088	0.000
TipoSocietario	0.126	1.000	0.068	0.064	0.055	0.000	0.125	0.000	0.000	0.000	0.135	0.472	0.000	0.000	0.162	0.050	0.061	1.000	0.081	0.000
anio_preinscripcion	0.119	0.068	1.000	1.000	0.011	0.000	0.000	0.000	0.055	0.000	0.000	0.342	0.189	0.125	0.099	0.079	0.029	0.999	0.332	0.041
antiguedad	0.136	0.064	1.000	1.000	0.023	0.077	0.000	0.000	0.304	0.000	0.011	0.380	-0.292	0.158	0.113	0.095	0.008	-0.976	0.102	0.181
cant_Apoderado	0.096	0.055	0.011	0.023	1.000	0.000	0.692	0.868	0.000	0.450	0.937	0.633	0.000	0.045	0.105	0.047	0.291	1.000	0.000	0.015
cant_antecedentes	0.000	0.000	0.000	0.077	0.000	1.000	1.000	NaN	-0.070	0.000	0.000	NaN	0.834	0.124	0.000	0.000	-0.088	-0.091	0.434	-0.052
cant_autenticado	0.121	0.125	0.000	0.000	0.692	1.000	1.000	0.475	0.000	0.427	0.688	0.306	1.000	0.000	0.096	0.051	0.091	1.000	0.090	0.000
cant_noAutenticado	0.240	0.000	0.000	0.000	0.868	NaN	0.475	1.000	0.000	0.448	0.841	1.000	NaN	0.132	0.000	0.281	0.554	1.000	0.000	0.000
cant_procesos_adjudicado	0.000	0.000	0.055	0.304	0.000	-0.070	0.000	0.000	1.000	0.000	0.000	1.000	-0.179	0.225	0.182	0.095	0.527	-0.284	0.000	0.375
cant_representante	0.263	0.000	0.000	0.000	0.450	0.000	0.427	0.448	0.000	1.000	0.836	1.000	0.000	0.000	0.532	0.000	0.000	1.000	0.329	1.000
cant_sinMontoLimite	0.099	0.135	0.000	0.011	0.937	0.000	0.688	0.841	0.000	0.836	1.000	0.294	0.000	0.035	0.106	0.037	0.254	1.000	0.037	0.000
cant_socios	0.216	0.472	0.342	0.380	0.633	NaN	0.306	1.000	1.000	1.000	0.294	1.000	NaN	0.000	1.000	0.336	1.000	1.000	1.000	1.000
cant_suspensiones	0.000	0.000	0.189	-0.292	0.000	0.834	1.000	NaN	-0.179	0.000	0.000	NaN	1.000	0.316	0.000	0.000	-0.205	0.256	0.000	0.005
dcant_procesos_adjudicado	0.108	0.000	0.125	0.158	0.045	0.124	0.000	0.132	0.225	0.000	0.035	0.000	0.316	1.000	0.228	0.165	0.076	0.070	0.064	0.128
dmonto_total_adjudicado	0.125	0.162	0.099	0.113	0.105	0.000	0.096	0.000	0.182	0.532	0.106	1.000	0.000	0.228	1.000	0.063	0.236	0.095	0.051	0.091
dtotal_articulos_provee	0.143	0.050	0.079	0.095	0.047	0.000	0.051	0.281	0.095	0.000	0.037	0.336	0.000	0.165	0.063	1.000	0.031	1.000	0.054	0.217
monto_total_adjudicado	0.035	0.061	0.029	0.008	0.291	-0.088	0.091	0.554	0.527	0.000	0.254	1.000	-0.205	0.076	0.236	0.031	1.000	0.004	0.000	0.134
periodo_preinscripcion	1.000	1.000	0.999	-0.976	1.000	-0.091	1.000	1.000	-0.284	1.000	1.000	1.000	0.256	0.070	0.095	1.000	0.004	1.000	0.918	-0.187
provincia	0.088	0.081	0.332	0.102	0.000	0.434	0.090	0.000	0.000	0.329	0.037	1.000	0.000	0.064	0.051	0.054	0.000	0.918	1.000	0.000
total_articulos_provee	0.000	0.000	0.041	0.181	0.015	-0.052	0.000	0.000	0.375	1.000	0.000	1.000	0.005	0.128	0.091	0.217	0.134	-0.187	0.000	1.000

Missing values

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

	CUIT	Nombre	FechaPreinscripcion	Estado	TipoSocietario	periodo_preinscripcion	anio_preinscripcion	cant_procesos_adjudicado	monto_total_adjudicado	antiguedad	provincia	cant_socios	cant_apercibimientos	cant_suspensiones	cant_antecedentes	cant_Apoderado	cant_representante	cant_autenticado	cant_noAutenticado	cant_sinMontoLimite	cant_MontoLimite	total_articulos_provee	dmonto_total_adjudicado	dcant_procesos_adjudicado	dtotal_articulos_provee	cluster_k_4
0	27236909900	EMR VENTAS & SERVICIOS	04/10/2016	Inscripto	Persona Física	201610	2016	68.0	1.069618e+07	5.0	Chubut	NaN	NaN	NaN	NaN	1.0	NaN	1.0	NaN	1.0	NaN	68.0	(9424898.401, 13557176.81]	(39.0, 1214.0]	(58.0, 97.6]	1
8	20305924076	Suministros EDA	13/10/2016	Inscripto	Persona Física	201610	2016	147.0	9.393091e+07	5.0	Ciudad Autónoma de Buenos Aires	NaN	NaN	NaN	NaN	2.0	NaN	1.0	1.0	2.0	NaN	107.0	(89439449.702, 222964579.98]	(39.0, 1214.0]	(97.6, 161.0]	1
9	20082883240	SEGUMAX de HORACIO MIGUEL ESPOSITO	18/10/2016	Desactualizado Por Documentos Vencidos	Persona Física	201610	2016	2.0	1.216063e+06	5.0	Ciudad Autónoma de Buenos Aires	NaN	NaN	NaN	NaN	1.0	NaN	1.0	NaN	1.0	NaN	263.0	(890758.9, 1302657.558]	(0.999, 2.0]	(161.0, 345.0]	1
13	20230506060	sin datos	15/08/2016	Inscripto	Persona Física	201608	2016	12.0	1.209260e+08	5.0	Ciudad Autónoma de Buenos Aires	NaN	NaN	NaN	NaN	1.0	NaN	1.0	NaN	1.0	NaN	5.0	(89439449.702, 222964579.98]	(8.0, 12.0]	(4.0, 6.0]	1
16	20141208269	sin datos	23/09/2016	Inscripto	Persona Física	201609	2016	1.0	6.407980e+05	5.0	Ciudad Autónoma de Buenos Aires	NaN	NaN	NaN	NaN	1.0	NaN	1.0	NaN	1.0	NaN	16.0	(599760.0, 890758.9]	(0.999, 2.0]	(15.0, 21.0]	1
30	20271472901	CONTRACTUAL	17/08/2016	Desactualizado Por Documentos Vencidos	Persona Física	201608	2016	1.0	1.900260e+05	5.0	Ciudad Autónoma de Buenos Aires	NaN	NaN	NaN	NaN	1.0	NaN	1.0	NaN	1.0	NaN	10.0	(104767.373, 224078.198]	(0.999, 2.0]	(8.0, 11.0]	1
32	20302787221	sin datos	30/07/2016	Desactualizado Por Documentos Vencidos	Persona Física	201607	2016	3.0	3.289500e+04	5.0	Ciudad Autónoma de Buenos Aires	NaN	NaN	NaN	NaN	1.0	NaN	1.0	NaN	1.0	NaN	8.0	(-0.001, 33011.111]	(2.0, 3.0]	(6.0, 8.0]	1
50	30546666707	UNIVERSIDAD NACIONAL DE LA PLATA	09/11/2016	Inscripto	Organismo Publico	201611	2016	29.0	1.624050e+09	5.0	Buenos Aires	NaN	NaN	NaN	NaN	1.0	1.0	2.0	NaN	2.0	NaN	21.0	(222964579.98, 46172150151.0]	(19.0, 39.0]	(15.0, 21.0]	1
56	20103522324	sin datos	21/10/2016	Inscripto	Persona Física	201610	2016	1.0	5.828571e+05	5.0	Mendoza	NaN	NaN	NaN	NaN	1.0	NaN	1.0	NaN	1.0	NaN	8.0	(377939.298, 599760.0]	(0.999, 2.0]	(6.0, 8.0]	1
99	20264053367	SERVISUR	21/10/2016	Inscripto	Persona Física	201610	2016	134.0	8.692312e+07	5.0	Buenos Aires	NaN	NaN	NaN	NaN	1.0	NaN	1.0	NaN	1.0	NaN	659.0	(46718747.516, 89439449.702]	(39.0, 1214.0]	(345.0, 6993.0]	1

	CUIT	Nombre	FechaPreinscripcion	Estado	TipoSocietario	periodo_preinscripcion	anio_preinscripcion	cant_procesos_adjudicado	monto_total_adjudicado	antiguedad	provincia	cant_socios	cant_apercibimientos	cant_suspensiones	cant_antecedentes	cant_Apoderado	cant_representante	cant_autenticado	cant_noAutenticado	cant_sinMontoLimite	cant_MontoLimite	total_articulos_provee	dmonto_total_adjudicado	dcant_procesos_adjudicado	dtotal_articulos_provee	cluster_k_4
10058	20385356243	DIAZ JONATAN MACIEL	13/09/2022	Inscripto	Persona Física	202209	2022	1.0	5.666667e+05	0.0	Chubut	NaN	NaN	NaN	NaN	1.0	NaN	1.0	NaN	1.0	NaN	1.0	(377939.298, 599760.0]	(0.999, 2.0]	(0.999, 2.0]	1
10059	20322310944	E.F.R.	26/08/2022	Inscripto	Persona Física	202208	2022	1.0	4.047619e+05	0.0	Jujuy	NaN	NaN	NaN	NaN	1.0	NaN	1.0	NaN	1.0	NaN	253.0	(377939.298, 599760.0]	(0.999, 2.0]	(161.0, 345.0]	1
10062	20149549987	TRANSPORTES ROBOL	07/02/2017	Desactualizado Por Mantencion Formulario	Persona Física	201702	2017	1.0	5.261905e+06	4.0	Corrientes	NaN	NaN	NaN	NaN	2.0	NaN	2.0	NaN	2.0	NaN	4.0	(4727330.113, 6702697.888]	(0.999, 2.0]	(3.0, 4.0]	1
10063	24925253304	ALBERTO FREDY MARTIN	15/02/2021	Inscripto	Persona Física	202102	2021	1.0	1.398857e+06	0.0	Buenos Aires	NaN	NaN	NaN	NaN	1.0	NaN	1.0	NaN	1.0	NaN	29.0	(1302657.558, 1793326.755]	(0.999, 2.0]	(21.0, 29.0]	1
10065	20328156742	M&M	01/09/2022	Inscripto	Persona Física	202209	2022	1.0	0.000000e+00	0.0	Corrientes	NaN	NaN	NaN	NaN	1.0	NaN	1.0	NaN	1.0	NaN	1.0	(-0.001, 33011.111]	(0.999, 2.0]	(0.999, 2.0]	1
10067	20171591563	BIOTECNIKA	16/06/2022	Inscripto	Persona Física	202206	2022	1.0	2.986090e+06	0.0	Buenos Aires	NaN	NaN	NaN	NaN	1.0	NaN	1.0	NaN	1.0	NaN	22.0	(2483085.385, 3396600.0]	(0.999, 2.0]	(21.0, 29.0]	1
10068	20293290416	ELIAS MARTIN SEGURA	26/08/2022	Inscripto	Persona Física	202208	2022	1.0	1.873469e+05	0.0	Ciudad Autónoma de Buenos Aires	NaN	NaN	NaN	NaN	1.0	NaN	1.0	NaN	1.0	NaN	1.0	(104767.373, 224078.198]	(0.999, 2.0]	(0.999, 2.0]	1
10069	20240423759	FEDERICO MARTIN NUÑEZ	26/08/2022	Inscripto	Persona Física	202208	2022	1.0	3.226531e+05	0.0	Ciudad Autónoma de Buenos Aires	NaN	NaN	NaN	NaN	1.0	NaN	1.0	NaN	1.0	NaN	1.0	(224078.198, 377939.298]	(0.999, 2.0]	(0.999, 2.0]	1
10071	20287286687	LAZARTE MARIO	03/08/2022	Inscripto	Persona Física	202208	2022	1.0	5.792102e+06	0.0	Buenos Aires	NaN	NaN	NaN	NaN	1.0	NaN	1.0	NaN	1.0	NaN	1.0	(4727330.113, 6702697.888]	(0.999, 2.0]	(0.999, 2.0]	1
10075	27331126530	sin datos	18/08/2022	Inscripto	Persona Física	202208	2022	1.0	9.367347e+04	0.0	Ciudad Autónoma de Buenos Aires	NaN	NaN	NaN	NaN	1.0	NaN	1.0	NaN	1.0	NaN	4.0	(33011.111, 104767.373]	(0.999, 2.0]	(3.0, 4.0]	1

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)